Data Mining and Decision Support: Integration and CollaborationDunja Mladenic, Nada Lavrač, Marko Bohanec, Steve Moyle Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting. |
From inside the book
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... selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision ... Selected methods and applications. The first two chapters cover data mining and the specific area of text and web ...
... selected data mining methods that proved useful in the applications described in this book. 1. INTRODUCTION Data mining (Fayyad, et al., 1996, Han and Kamber, 2001, Piatetski-Shapiro and Frawley, 1991) means “solving problems by ...
... Selected data mining applications are outlined in Section 4. The chapter concludes with a brief reflection on the role of data mining as a 'solution oriented” technology. 2. WHAT IS DATA MINING This section outlines a brief history of ...
... selection, as well as finding of useful properties/features, generating new features, defining appropriate feature values and/or value discretization. 4. Data mining modeling: the most important step of this process which is concerned ...
... SELECTED DATA MINING METHODS The most popular predictive data mining techniques are rule and decision tree learning techniques, which are mostly concerned with the discovery of classificatory properties of data tables. Data represented ...
Contents
| 1 | |
TEXT AND WEB MINING | 15 |
DECISION SUPPORT | 23 |
INTEGRATION OF DATA MINING AND DECISION | 37 |
COLLABORATION IN A DATA MINING VIRTUAL | 49 |
DATA MINING PROCESSES AND COLLABORATION | 63 |
AN INTRODUCTION | 80 |
SUPPORTING | 91 |
MINING 21 YEARS OF | 142 |
ANALYSIS OF A DATABASE OF RESEARCH PROJECTS | 157 |
WEBSITE ACCESS ANALYSIS FOR A NATIONAL | 167 |
FIVE DECISION SUPPORT APPLICATIONS | 177 |
COLLABORATIVE DATA MINING WITH RAMSYS | 215 |
LESSONS LEARNED FROM DATA MINING DECISION | 237 |
A KNOWLEDGE | 247 |
ACADEMIABUSINESS PARTNERSHIP MODELS | 261 |
PREPROCESSING FOR DATA MINING AND DECISION | 107 |
DATA MINING AND DECISION SUPPORT INTEGRATION | 118 |
APPLICATIONS OF DATA MINING | 131 |
Subject index 271 | 270 |